ReviewThe British journal of radiology2019
Role and future of MRI in radiation oncology.
Review in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed.
- Article
- Synthetic CT imaging for pelvic and abdominal MR-only radiotherapy: Clinical validation on a 1.5T MR-Linac.Journal of applied clinical medical physics · 2026Article
- Validating clinical feasibility of MRCAT and deep learning-based synthetic CT images for cervical cancer patient.Journal of applied clinical medical physics · 2025Article
- Feasibility of celiac axis delineation and treatment on combined magnetic resonance imaging and linear accelerator systems.Physics and imaging in radiation oncology · 2025Article
- Personalized federated learning for abdominal multi-organ segmentation based on frequency domain aggregation.Journal of applied clinical medical physics · 2025Article
- Clinical validation of MR-generated synthetic CT by MRCAT for brain tumor radiotherapy.Journal of applied clinical medical physics · 2025Article
- Hyperpolarized MRI theranostics in cancer.Frontiers in oncology · 2025Article
- Advancing gastrointestinal stromal tumor management: The role of imagomics features in precision risk assessment.World journal of gastrointestinal surgery · 2024Article
- AAPM Task Group 334: A guidance document to using radiotherapy immobilization devices and accessories in an MR environment.Medical physics · 2024Article
- Clinical implementation of a commercial synthetic computed tomography solution for radiotherapy treatment of glioblastoma.Physics and imaging in radiation oncology · 2024Article
- The Use of MR-Guided Radiation Therapy for Head and Neck Cancer and Recommended Reporting Guidance.Seminars in radiation oncology · 2024Review
- An integrated and fast imaging quality assurance phantom for a 0.35 T magnetic resonance imaging linear accelerator.Physics and imaging in radiation oncology · 2023Article
- The current and future role of the MRI radiographer in radiation oncology: A collaborative, experiential reflection on the Australian rollout of dedicated MRI simulators.Journal of medical radiation sciences · 2023Article
- Beyond diagnosis: is there a role for radiomics in prostate cancer management?European radiology experimental · 2023Review
- Evaluation of MRI-only based online adaptive radiotherapy of abdominal region on MR-linac.Journal of applied clinical medical physics · 2023Article
- Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience.Radiation oncology (London, England) · 2023Article
- MRI-LINAC: A transformative technology in radiation oncology.Frontiers in oncology · 2023Review
- Research progress on deep learning in magnetic resonance imaging-based diagnosis and treatment of prostate cancer: a review on the current status and perspectives.Frontiers in oncology · 2023Review
- The future of MRI in radiation therapy: Challenges and opportunities for the MR community.Magnetic resonance in medicine · 2022Review
- Tensor-valued diffusion magnetic resonance imaging in a radiotherapy setting.Physics and imaging in radiation oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Technical innovations and developments in areas such as disease localization, dose calculation algorithms, motion management and dose delivery technologies have revolutionized radiation therapy resulting in improved patient care with superior outcomes. A consequence of the ability to design and accurately deliver complex radiation fields is the need for improved target visualization through imaging. While CT imaging has been the standard of care for more than three decades, the superior soft tissue contrast afforded by MR has resulted in the adoption of this technology in radiation therapy. With the development of real time MR imaging techniques, the problem of real time motion management is enticing. Currently, the integration of an MR imaging and megavoltage radiation therapy treatment delivery system (MR-linac or MRL) is a reality that has the potential to provide improved target localization and real time motion management during treatment. Higher magnetic field strengths provide improved image quality potentially providing the backbone for future work related to image texture analysis-a field known as Radiomics-thereby providing meaningful information on the selection of future patients for radiation dose escalation, motion-managed treatment techniques and ultimately better patient care. On-going advances in MRL technologies promise improved real time soft tissue visualization, treatment margin reductions, beam optimization, inhomogeneity corrected dose calculation, fast multileaf collimators and volumetric arc radiation therapy. This review article provides rationale, advantages and disadvantages as well as ideas for future research in MRI related to radiation therapy mainly in adoption of MRL.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.